X-iPPGNet: A novel one stage deep learning architecture based on depthwise separable convolutions for video-based pulse rate estimation.

Pulse rate (PR) is one of the most important markers for assessing a person's health. With the increasing demand for long-term health monitoring, much attention is being paid to contactless PR estimation using imaging photoplethysmography (iPPG). This non-invasive technique is based on the analysis of subtle changes in skin color.

iPPG 2 cPPG: Reconstructing contact from imaging photoplethysmographic signals using U-Net architectures.

Imaging photoplethysmography (iPPG) is an optical technique dedicated to the assessment of several vital functions using a simple camera. Significant efforts have been made to reliably estimate heart and respiratory rates. Currently, research is focusing on the remote estimation of oxygen saturation and blood pressure (BP).